A virtual algorithm can fully utilize the characteristics of human eyes for spatial resolution to achieve a relatively high virtual resolution with respect to a specific subpixel arrangement under a relatively low physical resolution, by way of subpixel share, etc. It has such advantages as low power consumption, low process difficulty and high resolution, etc.
The core concept of the virtual algorithm is subpixel share. If a pixel position is lack of a subpixel of corresponding color, the way of subpixel share needs to be used to derive virtually the color that the position is lack of. If each derived virtual pixel can restore the input signal accurately, it indicates that this share algorithm can achieve a relatively high virtual resolution by using a relatively low physical resolution.
Some virtual algorithms also have disadvantages, for example, there will emerge colorful sides at image edges (color aliasing effect), and/or there will emerge sawtooth shapes, etc. at slash borders. Therefore it needs to continuously optimize and adjust these algorithms. In order to judge the merits of the algorithm, it needs to establish a set of stable evaluation system. A common practice is to calculate the RMS of the difference between corresponding pixels (as shown in the following formula). The smaller the RMS is, the smaller the difference between the output signal and the input signal is, and the higher the degree of reduction of the algorithm for the original picture is.
      1    N    ⁢            ∑      All        ⁢                  ⁢                                        (                                          R                out                            -                              R                                  i                  ⁢                                                                          ⁢                  n                                                      )                    2                +                              (                                          G                out                            -                              G                                  i                  ⁢                                                                          ⁢                  n                                                      )                    2                +                              (                                          B                out                            -                              B                                  i                  ⁢                                                                          ⁢                  n                                                      )                    2                    
Rout, Gout and Bout represent the strengths of red, green and blue pixels of the output signal, respectively, and Rin, Gin and Bin represent the strengths of red, green and blue pixels of the input signal, respectively.
In the present design, the practical pixel arrangement and the input pixels are not in a one-to-one correspondence relation. Therefore, it needs to convert the practical pixel arrangement into virtual pixels, so as to be able to appraise the algorithm by RMS. The present design is to simulate how a practical pixel is converted into a virtual pixel based on a model established based on the subjective feelings of the human eye.